{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["33"],"submitter":["Wang LH"],"pubmed_abstract":["The quality variation of <i>Goji</i> berry across cultivated zones leaded to an urgent requirement of geographical discrimination. Classical untargeted to targeted strategy faced with the problem of reducing prediction capability. Here, a new untargeted to targeted transition strategy was proposed. At first, the AntDAS-GCMS was used for automatically resolving compounds in untargeted metabolic profiling data to initialize a biomarker set. Compounds with similar chemical structures and/or homologous metabolic pathways were introduced to enhance the coverage of biomarker set, which were used to construct an MRM-based targeted metabolomics method. Quantitative analysis revealed that, proline was dramatically higher in Gansu (252.31 ± 310.68 μg/g) than Ningxia (1.85 ± 4.56 μg/g) and Xinjiang ("],"journal":["Food chemistry: X"],"pagination":["103549"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC12853052"],"repository":["biostudies-literature"],"pubmed_title":["A combination of automatic untargeted metabolic profiling analysis with targeted metabolomics to enhance geographical discrimination of &lt;i&gt;Goji&lt;/i&gt; berry."],"pmcid":["PMC12853052"],"pubmed_authors":["Liu PP","Wen YJ","Zhang Y","Lv Y","Wang LH","Zhai M","Zhou HN","Li SF","Yu YJ","Wang WX","Zheng QX"],"additional_accession":[]},"is_claimable":false,"name":"A combination of automatic untargeted metabolic profiling analysis with targeted metabolomics to enhance geographical discrimination of &lt;i&gt;Goji&lt;/i&gt; berry.","description":"The quality variation of <i>Goji</i> berry across cultivated zones leaded to an urgent requirement of geographical discrimination. Classical untargeted to targeted strategy faced with the problem of reducing prediction capability. Here, a new untargeted to targeted transition strategy was proposed. At first, the AntDAS-GCMS was used for automatically resolving compounds in untargeted metabolic profiling data to initialize a biomarker set. Compounds with similar chemical structures and/or homologous metabolic pathways were introduced to enhance the coverage of biomarker set, which were used to construct an MRM-based targeted metabolomics method. Quantitative analysis revealed that, proline was dramatically higher in Gansu (252.31 ± 310.68 μg/g) than Ningxia (1.85 ± 4.56 μg/g) and Xinjiang (","dates":{"release":"2026-01-01T00:00:00Z","publication":"2026 Jan","modification":"2026-06-19T04:59:47.358Z","creation":"2026-06-19T03:07:24.707Z"},"accession":"S-EPMC12853052","cross_references":{"pubmed":["41623981"],"doi":["10.1016/j.fochx.2026.103549"]}}